Optimal control based seizure abatement using patient derived connectivity
Epilepsy is a neurological disorder in which patients have recurrent seizures. Seizures occur in conjunction with abnormal electrical brain activity which can be recorded by the electroencephalogram (EEG). Often, this abnormal brain activity consists of high amplitude regular spike-wave oscillations...
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sg-ntu-dr.10356-1060492022-02-16T16:29:18Z Optimal control based seizure abatement using patient derived connectivity Taylor, Peter N. Thomas, Jijju Sinha, Nishant Dauwels, Justin Kaiser, Marcus Thesen, Thomas Ruths, Justin School of Electrical and Electronic Engineering DRNTU::Science::Biological sciences::Human anatomy and physiology::Neurobiology Epilepsy is a neurological disorder in which patients have recurrent seizures. Seizures occur in conjunction with abnormal electrical brain activity which can be recorded by the electroencephalogram (EEG). Often, this abnormal brain activity consists of high amplitude regular spike-wave oscillations as opposed to low amplitude irregular oscillations in the non-seizure state. Active brain stimulation has been proposed as a method to terminate seizures prematurely, however, a general and widely-applicable approach to optimal stimulation protocols is still lacking. In this study we use a computational model of epileptic spike-wave dynamics to evaluate the effectiveness of a pseudospectral method to simulated seizure abatement. We incorporate brain connectivity derived from magnetic resonance imaging of a subject with idiopathic generalized epilepsy. We find that the pseudospectral method can successfully generate time-varying stimuli that abate simulated seizures, even when including heterogeneous patient specific brain connectivity. The strength of the stimulus required varies in different brain areas. Our results suggest that seizure abatement, modeled as an optimal control problem and solved with the pseudospectral method, offers an attractive approach to treatment for in vivo stimulation techniques. Further, if optimal brain stimulation protocols are to be experimentally successful, then the heterogeneity of cortical connectivity should be accounted for in the development of those protocols and thus more spatially localized solutions may be preferable. Published version 2015-06-29T02:47:04Z 2019-12-06T22:03:41Z 2015-06-29T02:47:04Z 2019-12-06T22:03:41Z 2015 2015 Journal Article Taylor, P. N., Thomas, J., Sinha, N., Dauwels, J., Kaiser, M., Thesen, T., et al. (2015). Optimal control based seizure abatement using patient derived connectivity. Frontiers in Neuroscience, 9, 202-. 1662-453X https://hdl.handle.net/10356/106049 http://hdl.handle.net/10220/26113 10.3389/fnins.2015.00202 26089775 en Frontiers in Neuroscience © 2015 Taylor, Thomas, Sinha, Dauwels, Kaiser, Thesen and Ruths. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. application/pdf |
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DRNTU::Science::Biological sciences::Human anatomy and physiology::Neurobiology Taylor, Peter N. Thomas, Jijju Sinha, Nishant Dauwels, Justin Kaiser, Marcus Thesen, Thomas Ruths, Justin Optimal control based seizure abatement using patient derived connectivity |
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Epilepsy is a neurological disorder in which patients have recurrent seizures. Seizures occur in conjunction with abnormal electrical brain activity which can be recorded by the electroencephalogram (EEG). Often, this abnormal brain activity consists of high amplitude regular spike-wave oscillations as opposed to low amplitude irregular oscillations in the non-seizure state. Active brain stimulation has been proposed as a method to terminate seizures prematurely, however, a general and widely-applicable approach to optimal stimulation protocols is still lacking. In this study we use a computational model of epileptic spike-wave dynamics to evaluate the effectiveness of a pseudospectral method to simulated seizure abatement. We incorporate brain connectivity derived from magnetic resonance imaging of a subject with idiopathic generalized epilepsy. We find that the pseudospectral method can successfully generate time-varying stimuli that abate simulated seizures, even when including heterogeneous patient specific brain connectivity. The strength of the stimulus required varies in different brain areas. Our results suggest that seizure abatement, modeled as an optimal control problem and solved with the pseudospectral method, offers an attractive approach to treatment for in vivo stimulation techniques. Further, if optimal brain stimulation protocols are to be experimentally successful, then the heterogeneity of cortical connectivity should be accounted for in the development of those protocols and thus more spatially localized solutions may be preferable. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Taylor, Peter N. Thomas, Jijju Sinha, Nishant Dauwels, Justin Kaiser, Marcus Thesen, Thomas Ruths, Justin |
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Article |
author |
Taylor, Peter N. Thomas, Jijju Sinha, Nishant Dauwels, Justin Kaiser, Marcus Thesen, Thomas Ruths, Justin |
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Taylor, Peter N. |
title |
Optimal control based seizure abatement using patient derived connectivity |
title_short |
Optimal control based seizure abatement using patient derived connectivity |
title_full |
Optimal control based seizure abatement using patient derived connectivity |
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Optimal control based seizure abatement using patient derived connectivity |
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Optimal control based seizure abatement using patient derived connectivity |
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optimal control based seizure abatement using patient derived connectivity |
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2015 |
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https://hdl.handle.net/10356/106049 http://hdl.handle.net/10220/26113 |
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